Cavity Microelectrode Arrays for Electrical Recordings From Neurons

Advanced Electronic Materials, vol. 12

Abstract

ABSTRACT Microelectrode arrays (MEAs) are tools for investigating the electrophysiological activity of cardiac and neuronal cell networks with single‐cell resolution in a highly parallelized manner. Yet, the signal quality obtained from such measurements is usually limited compared to intracellular measurements as provided by the patch clamp technique, the gold standard for electrophysiology. As a consequence, different approaches are currently investigated for improving the signal and signal‐to‐noise ratio (SNR) in extracellular measurement setups. One approach relies on the fabrication of cavity microelectrode arrays (C‐MEAs), in which a liquid‐filled cavity with a nanoscale height (∼100 nm) is formed above the electrode. C‐MEAs improve signal‐to‐noise ratios for small electrode systems by providing an effectively increased electrode‐electrolyte interface and consequently reduced impedance without loss of lateral resolution. In this study, we show how the geometry of cavity electrode systems affects sealing properties by using a human embryonic kidney (HEK) cell model. We further demonstrate extracellular recordings of action potentials from primary neuronal cells and elucidate the impact of the electrode geometry in terms of signal amplitude and SNR.

Authors 3

1. Johannes Lewen Aachen

   RWTH Aachen University · Forschungszentrum Jülich

   Affiliation as printed

   Bioelectronics Institute of Biological Information Processing‐3 Forschungszentrum Jülich Jülich Germany

   RWTH Aachen University Aachen Germany

2. Bernhard L. Wolfrum

   Technical University of Munich

   Affiliation as printed

   Neuroelectronics Munich Institute of Biomedical Engineering School of Computation, Information and Technology Technische Universität München Garching Germany

3. Andreas Offenhäusser corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Bioelectronics Institute of Biological Information Processing‐3 Forschungszentrum Jülich Jülich Germany